Cathleen M. Stützer

Academic Analytics | University Development | Data & Decision Intelligence

My guiding principle: “Data do not explain the world. But they help us ask the right questions, uncover meaningful patterns, and make better decisions.”

I work at the intersection of data, decision-making, and university development. My focus lies in developing evidence-based foundations for strategic decision-making in higher education and research organizations.

Drawing on extensive experience in research, quality management, data analytics, and strategic university development, my current work centers on the design and implementation of data-informed decision-making and governance processes in higher education.

Over many years, I held research and leadership positions and led projects in the fields of Learning Analytics, Academic Analytics, Digital Higher Education, Artificial Intelligence, and Computational Social Science.

My professional perspective combines scientific inquiry, organizational development, and data-informed governance. As a result, I deliberately operate at the interface between research, higher education management, and strategic transformation.

My areas of expertise include:

• Academic Analytics
• Evidence-Based University Development
• Higher Education Governance and Data Strategy
• Digital Transformation
• Learning Analytics and Artificial Intelligence in Higher Education
• Network Science and Computational Social Science

Over the years, I have actively contributed to academic communities through leadership roles in professional associations, editorial responsibilities for scientific publication series, and the organization of international conferences and workshops.

My goal is to make data, analytics, and scientific evidence actionable in ways that support strategic decision-making, organizational learning, and sustainable development within higher education institutions.

Selected Publications

Foundational work on Social Academic Analytics, Network Science, and collaborative learning systems (2011–2013) laid the groundwork for my later research on Learning Analytics, Artificial Intelligence in Higher Education, and Academic Analytics.

Strategic Contributions

Academic Analytics, 25.03.2026, TUD Miteinanderklausur, TU Dresden

Academic Analytics. Erfolgsfaktoren und Herausforderungen bei der Implementierung datengetriebener Hochschulsteuerung, 17.-19.09.2024, Zwischen Komplexitätsreduktion und Zauberei: Strategisch relevante Daten für Entscheidungsträger*innen an Hochschulen bereitstellen, visualisieren, verständlich machen, Universität Bielefeld, Tagungsprogramm

Academic Analytics, 27.03.2025, TUD Miteinanderklausur, TU Dresden

Evidenzbasierte Universitätsentwicklung. Innovatives Steuern für die Zukunft des Hochschulsektors, 23.-25.09.2024, Jahrestagung der Gesellschaft für Hochschulforschung (GFHF), Feruniversität Hagen, Tagungsprogramm

Academic Analytics. DE-Executive One Page (Dresden, 28.09.2025)

Academic Analytics. EN-Executive One Page (Dresden, 28.09.2025)

Foundational Contributions

• Stuetzer, C. M., Breiger, R., & Koehler, T. (2013). Social Academic Analytics in Higher Education.
• Stuetzer, C. M., Koehler, T., Carley, K. M., & Thiem, G. (2013). Brokering Behavior in Collaborative Learning Systems. DOI: https://doi.org/10.1016/j.sbspro.2013.10.702
• Stuetzer, C. M., Carley, K. M., Koehler, T., & Thiem, G. (2011). The Communication Infrastructure During the Learning Process in Web-Based Collaborative Learning Systems. DOI: https://doi.org/10.1145/2527031.2527045

Academic Analytics & Hochschulentwicklung

• Stützer, C. M. (2017). Academic Analytics: Zur Bedeutung von (Big) Data Analytics in der Evaluation.
• Stuetzer, C. M., Breiger, R., & Koehler, T. (2013). Social Academic Analytics in Higher Education.

Künstliche Intelligenz & Hochschulbildung

• Stützer, C. M. (2022). Künstliche Intelligenz in der Hochschullehre. DOI: https://doi.org/10.25368/2022.12
• Stützer, C. M., & Kravčík, M. (2023). Künstliche Intelligenz in der Hochschulbildung. DOI: https://doi.org/10.1007/978-3-658-40079-8

Learning Analytics

• Gaaw, S., & Stuetzer, C. M. (2020). A Proactive Perspective on the Future of Learning Analytics. https://www.solaresearch.org/wp-content/uploads/2020/06/LAK20_Companion_Proceedings.pdf
• Stützer, C. M., Winter, J., & Jablonka, M. (2020). Blended Learning Analytics (II) – Text als Wissensspeicher. https://zfe.hszg.de/fileadmin/NEU/Redaktion-Zfe/Dateien/wel/wel20/Tagungsband_WeL20.pdf

Computational Social Science & Network Science

• Stuetzer, C. M., Welker, M., & Egger, M. (2018). Big Data Analytics: Obstacles and Opportunities for Social Science. https://www.halem-verlag.de/wp-content/uploads/2017/03/9783869622675_le.pdf
• Stuetzer, C. M., Koehler, T., Carley, K. M., & Thiem, G. (2013). Brokering Behavior in Collaborative Learning Systems. https://doi.org/10.1016/j.sbspro.2013.10.702

Herausgeberschaften

• Tabino, O., Stützer, C., & Wachenfeld-Schell, A. (Eds.) (2021). Data Visualization in Social Science and Market Research. https://doi.org/10.25368/2021.91
• Stützer, C. M., Frohwieser, D., & Lenz, K. (Eds.) (2020). Potentiale und Herausforderungen digitaler Hochschulbildung. https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-720292
• Stuetzer, C. M., Welker, M., & Egger, M. (Eds.) (2018). Computational Social Science in the Age of Big Data. https://www.halem-verlag.de/computational-social-science-in-the-age-of-big-data/